MIT invents algorithm to diagnose Parkinson's disease

MIT invents algorithm to diagnose Parkinson’s disease

A team of researchers from the renowned Massachusetts Institute of Technology (MIT) has developed methods for early detection of Parkinson’s disease. They reflect how the brain works, based on the patient’s breathing pattern.

This was a major discovery at the prestigious MIT. As reported by the newspaper Uzbek & Riga, a team of researchers from this valuable knowledge base has succeeded in developing an artificial neural network that can diagnose Parkinson’s disease at an early stage. Consisting of several algorithms linked together to mimic human brain activity, it is based on the analysis of patients’ breathing patterns to predict the presence of disease.

If this discovery turns out to be capital, this neurodegenerative disease will be very difficult to diagnose. The first symptoms (extreme episodic fatigue, muscle stiffness, tremors) actually appear many years after the disease is declared and at this stage, it is the only way to detect it. Other methods are “invasive, expensive and require access to specialized medical centers, making them unsuitable for early diagnosis or frequent tests that allow continuous monitoring of disease progression,” MIT’s researchers explain.

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25,000 new cases per year

The development of this technology is important because Parkinson’s is “the fastest growing neurological disease in the world.” Yet according to Usbek & Rica, it has already affected 167,000 people in France in 2015. In addition, 25,000 new cases are diagnosed every year.

As Dina Katabi, one of the researchers at MIT, said, this artificial neural network “makes it possible to conduct clinical trials of significantly shorter duration and with fewer participants, which ultimately accelerates the development of new therapies.” At this point, there is no treatment to stop or reverse Parkinson’s disease. Last but not least, “this new diagnostic approach may aid in the evaluation of patients with Parkinson’s disease in traditionally disadvantaged communities, including those living in rural areas and those who have difficulty leaving home due to limited mobility or cognitive impairment.” A real ray of hope for the suffering patients and their families.

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